Method, apparatus, electronic device, medium, and program product for monitoring status of production order

Abstract

Various embodiments include a method for monitoring the status of a production order in a factory. The method may include: generating a production IoT model based on a production scheduling system document, the production IoT model comprising a first set process attributes of product processing; generating a product IoT model based on a product design specification document, the product IoT model comprising the first set of process attributes of product processing; associating the production IoT model with the product IoT model; learning data of a production device acquired by a data acquisition automation control system in the factory to obtain a data model representing processing steps of a product; and matching the processing steps against the process attributes of the product IoT model and determining the status of the production order in the factory based on the matching result.

What is claimed is: 
     
       1. A method for monitoring the status of a production order in a factory, the method comprising:
 generating a production IoT model based on a production scheduling system document, the production IoT model comprising a first set of process attributes of product processing; 
 generating a product IoT model based on a product design specification document, the product IoT model comprising the first set of process attributes of product processing; 
 associating the production IoT model with the product IoT model; 
 learning data of a production device acquired by a data acquisition automation control system in the factory to obtain a data model representing processing steps of a product; and 
 matching the processing steps against the process attributes of the product IoT model and determining the status of the production order in the factory based on the matching result. 
 
     
     
       2. The method as claimed in  claim 1 , wherein generating the production IoT model on the basis of the production scheduling system document comprises generating a production IoT model for each order number in the production scheduling system document. 
     
     
       3. The method as claimed in  claim 1 , wherein generating the product IoT model on the basis of a product design specification document comprises extracting product metadata from a software design tool to generate the product IoT model. 
     
     
       4. The method as claimed in  claim 1 , wherein matching the processing steps against the process attributes of the product IoT model and determining the status of the production order in the factory on the basis of the matching result comprises determining the product and an order number the current device processes according to the production IoT model and the product IoT model if a data change of the processing steps in the data model matches the process attributes of the product IoT model. 
     
     
       5. The method as claimed in  claim 1 , wherein the data acquisition automation control system comprises at least one of a vibration sensor, a current sensor, a temperature sensor and a humidity sensor. 
     
     
       6. The method as claimed in  claim 1 , wherein learning data of a production device acquired by a data acquisition automation control system in the factory to obtain a data model representing processing steps of a product comprises using a data clustering engine to learn the data to obtain a data model representing processing steps of a product on the basis of at least one of the change time of data, the change period of data and the amplitude of data. 
     
     
       7. An electronic device comprising:
 a processor; and 
 a memory coupled with the processor, the memory configured to store instructions, wherein when the instructions are executed by the processor, cause the processor to: 
 generate a production IoT model based on a production scheduling system document, the production IoT model comprising a first set of process attributes of product processing; 
 generate a product IoT model based on a product design specification document, the product IoT model comprising the first set of process attributes of product processing; 
 associate the production IoT model with the product IoT model; 
 learn data of a production device acquired by a data acquisition automation control system in the factory to obtain a data model representing processing steps of a product; and 
 match the processing steps against the process attributes of the product IoT model and determining the status of the production order in the factory based on the matching result. 
 
     
     
       8. The electronic device as claimed in  claim 7 , wherein the instructions further cause the processor to generate a production IoT model for each order number in the production scheduling system document. 
     
     
       9. The electronic device as claimed in  claim 7 , wherein the instructions further cause the processor to extract product metadata from a software design tool to generate the product IoT model. 
     
     
       10. The electronic device as claimed in  claim 7 , wherein the instructions further cause the processor to determine the product and the order number the current device processes according to the production IoT model and the product IoT model if a data change of the processing steps in the data model matches the process attributes of the product IoT model. 
     
     
       11. The electronic device as claimed in  claim 7 , wherein the data acquisition automation control system comprises at least one of a vibration sensor, a current sensor, a temperature sensor and a humidity sensor. 
     
     
       12. The electronic device as claimed in  claim 7 , wherein the instructions further cause the processor to use a data clustering engine to learn the data to obtain a data model representing processing steps of a product on the basis of at least one of the change time of data, the change period of data, and the amplitude of data.